THE BASICS

How much could a data union member earn?

This is a great question. So let’s start by saying we ultimately don’t know. But most models assume that people will join just one DU. Or it’ll be just Facebook data that is monetised. We should throw that assumption out the window as we already have DUs in our ecosystem representing many different types of data. Most individuals could join all of them in under 10 minutes. There are also different things data union operators can do for you to monetise your data. The first is to sell raw data sets. The second is to join forces with other DUs to create analytics. The third revenue stream is to enable individuals to store their own streams of data they are creating and then, should people choose, to allow advertisers, or other service providers, to read those sets in return for payment. These are markets worth hundreds and hundreds of billions.  

Of course, entry into a data union will in the end likely be somewhat gated. All that will be needed for viable data sets is a sample of the overall population, not everyone.  This is known as a panel. So the smaller the viable ‘panel’ size, the higher the individual reward. And then finally you have to factor in growing demand from data hungry vertices like AI/ML into the mix. Here is a quantitative piece of research that tackles what individuals might expect to fetch for their data. But our guesstimate is that in a few years, individuals joining 4-5 data unions will earn more than $100 per annum in passive income. Combined with the services that will be provided from controlling your own data, the ultimate value will feel like a lot more.  

How does an online user join a data union?

There’s no one way to join/onboard to a data union. That versatility is a very positive feature. So far the main models have been these: 

  • Browser plugins 
  • Mobile apps 
  • Web-based sign-up. 

Members will often check in to their wallet on a DU to see how much they have earned. We expect some basic governance and member preference features to be added into all DUs. Through our unitary wallet, DU members will also be able to store the same stream of data that is sent to the DU, in a decentralised storage vault. 


ABOUT POOL

Does Pool want to be a framework for commercialising data transactions, so that data owners can get the value of their data?

This is right. In essence we are layer 1 for the data unions themselves, providing them with all the tools they need to be successful. In return Pool takes a cut of that revenue to ensure more data union growth and the upkeep and development of the framework.

There are also many other data unions in the ecosystem who we are currently talking to and they are aware of our proposition and would like to transfer to Pool once they can view our stack and the features we offer. 

What stage is Pool at?

We now have a brand, a core team of more than a dozen employees, seed funding and we are well into product development. You can view our roadmap here: https://pooldata.io/product-roadmap/ 

In total, the core team brings together more than 12 years of direct experience on data union development, including co-creating a v1 framework, and helping to build and kick-start various data unions to date including Swash. We’ve started Pool to focus on DUs entirely, now that the market conditions are optimal.

We have a holistic plan for scaling from the buyers’ side and the DU operators’ (DUO) side and hope to raise another $20m+ in the next two quarters to enable this vision. We expect to release our v1 Marketplace by Q2 2022.

Where do you envisage the growth of new data unions coming from? Will it be new data unions, or companies creating their own data unions from existing user bases, or something else?

Initially, Pool expects most growth of the general ecosystem to come from new data unions (DUs) helping people to monetise their data. The reasons for this are multifarious:

1. In our team’s two-year enterprise outreach experience across various industry verticals (eg music and mobile communications), we’ve found enterprises are too slow to respond to the challenge of the new data paradigm. 

  • Departments – legal, marketing, data science, innovation etc – are often not aligned
  • The ultimate revenue streams generated by such activities are not large enough to incentivise establishing company-wide change
  • Regulatory evolution has not been clear (until now) 
  • When applicable, selling raw data streams can be viewed internally as a threat to that platform’s advertising delivery model
  • Siloing data is instinctive; monetising it is not.

2. Data unions have natural product advantages over enterprise-led models. Data products formed of streams from multiple outlets are far more valuable than single company outputs, eg a data union made up of a member’s Spotify, Audible and iTunes data creates far more value than only, say, Spotify selling permissioned streams from members who explicitly consent to third-party data sales.

How does Pool solve the data pricing problem on its marketplace?

Firstly, everything is priced in USD. That helps a lot, especially compared to other crypto data market solutions. Secondly, the DUs themselves fix the price. So for the time being it’s easy enough for DUs to price their products competitively. Finally on this – and this is the short version here – we work with the buyers to really assess and set prices that again are competitive. CPM or consumers per mille (thousand) is also a standardised way of pricing data sets.

A publisher’s ability to provide quality free content is based on an exchange (attaining customer consent, using their onsite behaviours to then monetise it). How does a data union impact this publishing model?

Data unions (and more so the enabling EU legislation) will affect those whose revenue model is significantly dependent on either brokering personal data to third parties or creating third-party analytics solutions based on their first-party data. However, the number of those companies/platforms is actually very small. (We wouldn’t count FB and Google as publishers in the traditional sense.) For many other businesses, there will be minimal downsides along with significant ecosystem upsides over the medium to long term. Of course, porting data to a data union doesn’t in and of itself remove that data from the original platform. It just moves a copy of that information into an organisation that can also derive value from it, but this time on behalf of the data creator.

With regards to Facebook, Google, Amazon or other walled gardens – does a data union impact those organisations, and if so, in what way?

When draft provisions of the Digital Markets Act come into law, ie when realtime data portability from APIs is enacted on gatekeepers, then it is sort of game over for Google’s data silos when you combine this with a data union.

We believe that we could create between five and ten separate DUs from Google’s output alone.

Facebook is a special case largely because the data structures are so unique and also so integrated in a co-social way with other users/data creators. It’s not immediately obvious how DUs will be able to simply broker raw FB data in its entirety but there are specialised DU innovators we have been talking with who believe they are ready for just this challenge.

Can you give more details on the payment mechanism?

The payment mechanism is pretty simple. Buyers – analytics companies, enterprises AI/ML, hedge funds etc – pay for the data product (a realtime subscription or static historical data) through normal banking channels. Once transferred, and using open banking facilities, this is converted into an equivalent amount of USD-denominated stable coin in the backend. That sum is then automatically sent to an Ethereum smart contract. This smart contract is key as it governs the membership of the DU and also the other parties to whom money must be disbursed including  the DU operators and the Pool Foundation.

Why a stable coin? Because we want to ensure pricing and reward consistency for all parties. Why crypto? The answer is that no fiat system can handle these levels of micro-payments to this number of people, so seamlessly, and at such incredibly low cost. Which partly explains why DUs have only just gotten off the ground. This is a technically led innovation. 

Also, digital, programmable money is the future of payments. Why build for the past?

Will any part of the Pool infrastructure be centralised?

Yes. Web3 can’t yet handle decentralised p2p messaging, for example. Other parts of the stack will also be centralised (ie the analytics solution). Pool doesn’t believe in technical decentralisation above operative functionality. Other projects we have all worked at have really suffered because of ideological purity in that regard and in doing so, wasted tons of capital, time and even now have yet to create functioning, let alone well adopted, products. When suitable Web3 technologies are released, we will be the first to adopt them. We do believe that our consumer-facing product (our data wallet) can be decentralised from day one and that will help guarantee users are as in control as possible.

Where is your data stored?

So for the aggregated (and pseudonymised) data, the DU itself holds that information and serves it up as a static file (or as a realtime API) on Pool’s marketplace. Pool in that regard doesn’t store any data. When we release our data wallet, that will have a personal data vault (PDV) added, which will help store the data that users create from a DU and basically copy and paste that realtime information into the PDV. That solution will be non-custodial (from Pool’s perspective) and will be controlled and operated by the user using the same public/private key as the wallet.

Token governance will kick in after 20-30 months. Which type of decisions will governance have a say in?

We haven’t fully decided that as yet. DUOs will at first take decisions that directly mostly affect them, eg new feature changes on the marketplace, data protocols etc. That will rapidly move to fiscal decisions for the platform, like how the analytics revenue should be divided up. But wherever we start won’t be where we end up. The idea would be to progressively decentralise the governance of the whole platform to its stakeholders.


ETHICS & REGULATION

Is there a clash between the two objectives over privacy and sharing value?  One discourages sharing, the other motivates.

A pithy answer might be this: while there may in essence be a prima facie clash, digital users can only truly value their privacy if they understand the value of what they are giving up, and do in fact have some semblance of control over that data in the first place. Otherwise the paradigm is a false one.

A longer more considered answer can be found here: Privacy is dead. Long live data ownership. Part 2 is here. The essays argue that sharing data in a positive, consensual fashion helps separate what is genuinely private vs what is worth sharing. Overall, the effect is to enhance privacy.

Do data unions really help protect privacy or are they more focused on changing who controls data and sharing the value of data?

Again, I’d refer to the essay (esp part 2). And then add this summation: pursuing privacy as a singular policy goal has entrenched monopolies, disempowered citizens, increased inequality, stymied innovation and most of all, somehow still permitted the greatest monitoring of humanity in recorded history. 

So the primary goal of a data union is not to protect privacy but to empower data creators. Privacy is absolutely part of that because it is part of data dignity, but not the only part. This framing mirrors more closely how humans behave. We aren’t privacy-centric beings. We are social ones. We share information all the time. But we like to share personal information on our own terms. Privacy tech has been great at allowing people to say no to sharing data. But terrible at enabling people to say yes. The new data economy needs to reflect that. 

With that said, how specifically do DUs protect privacy?

  1. Members of DUs only join the entity if they want to monetise/share/license their data  to begin with.
  2. Members  control the level of information they are comfortable with sharing, inside the given DU interface. 
  3. Aggregated data sets confer a level of pseudonymity.
  4. A DU operator acts as a professional agent working on behalf of the member not just to return best value for their data but also to ensure privacy and other outcomes over the long term.  
  5. Pool does not have access to the data. 
  6. Privacy enhancing tech (PET) is getting better all the time. We will use a zero knowledge set-up when it comes to individuals storing their own personal data, which – with only their explicit opt-in through their key signature – can be read by service providers including advertisers.
Does a data union have exclusive access to an individual’s data or can an individual join many data unions? And what stops a data union becoming just another walled garden?

Currently an individual can join many DUs. But there are those arguing for more comprehensive data union legislation that will create a legal framework for the former

What stops a DU being another walled garden is legislation. The EU machine is right now in the midst of hammering this out but essentially the idea is to create an independent raw data layer. The two provisions in the Data Governance Act (DGA) that achieve that are:

  1. Article 11 (1): the provider may not use the data for which it provides services for other purposes than to put them at the disposal of data users and shall provide data intermediation services through a separate legal person. In short the regulation will ensure that DUs, or data co-operatives or intermediaries as they refer to them in the DGA, will not be able to sell analytics services. Effectively what we’ll see is the creation of an independent raw data layer in Europe. 
  2. Fiduciary duties imposed by the DGA on DUs will mean that they will have a legal obligation to return best value for their members. Given the above, this in effect means selling the raw data to as many whitelisted vendors as possible.

    You can read more about that here: https://pooldata.io/blog/the-end-of-data-monopolies/
Data trading is often a licensed activity. What’s the regulatory policy in the region where Pool plans to operate, and does Pool need to spend effort solving this problem?

The regulatory environment is changing rapidly. What is happening in the EU right now is that DUs will be registered under a new act (the Data Governance Act), which is yet to come into force. The act talks about data co-operatives/intermediaries (ie data unions) and will set out how they get registered. This, we believe, will change the regulatory environment around the world as consumers see the benefit of being paid for their data.  

We have also onboarded a chief strategic officer whose role it is to look at policy around the globe. Our main target market in terms of data sales will be the EU for the next year ahead. However, Southeast Asia is a very promising market and Japan and India have very interesting data legislation, which may enable DUs to prosper.